Cryptocurrency Sectorization through Clustering and Web-Scraping: Application to Systematic Trading

Abstract

Although they are presented as a hypothesis, the authors discuss the historical events that have led to the rise of cryptocurrencies as a legitimate new asset class. They also discuss issues around cryptocurrency fundamentals as a means to explain the lack of sectors that exists for other asset classes such as equities or commodities. To address this issue, they propose a new methodology based on a hybrid approach between k-means and hierarchical clustering with alternative data gathered from web-scraping. The authors then reintroduce a couple of mathematical models, namely risk parity and momentum. Finally, they test their geopolitical hypothesis through a long-only strategy using risk parity and test their abstract sectorization through a long–short strategy.